black-scholes-NN

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black-scholes-NN

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Paper published in the Journal of Investment Management, co-authored with Sanjiv R. Das

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### Abstract

Modern advancements in mathematical analysis, computational hardware and software, and availability of big data have made possible commoditized ma- chines that can learn to operate as investment managers, financial analysts, and traders. We briefly survey how and why AI and deep learning can influence the field of Finance in a very general way. Revisiting original work from the 1990s, we summarize a framework within which machine learning may be used for finance, with specific application to option pricing. We train a fully-connected feed-forward deep learning neural network to reproduce the Black and Scholes (1973) option pricing formula to a high degree of accuracy. We also offer a brief introduction to neural networks and some detail on the various choices of hyper-parameters that make the model as accurate as possible. This exercise suggests that deep learning nets may be used to learn option pricing models from the markets, and could be trained to mimic option pricing traders who specialize in a single stock or index.

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